Exposure data generation method and device, exposure data verification method and device and storage medium

ABSTRACT

Exposure verification is applied to exposure data indicating a pattern to be exposed by a charged particle beam. If an error point is extracted from the exposure data by the exposure verification, the values of coefficients are modified and exposure data is regenerated taking into consideration the coefficients whose values have been modified. Thus, exposure data is re-generated by changing each of the coefficient values within its appropriate range.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based upon and claims the benefit of priority fromthe prior Japanese Patent Application No. 2006-037006 filed on Feb. 14,2006, the entire contents of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a technology for generating exposuredata to expose a resist film formed on a multi-layered semiconductorsubstrate by a charged particle beam.

2. Description of the Related Art

Lately, in the manufacture of semiconductor devices, such as alarge-scale integrated circuit (LSI) and the like, it is desired to forma very fine pattern. Thus, currently a charged particle beam is usuallyused for pattern generation exposure. It is common to use an electronfor a charged particle.

By charged particle beam exposure, a part of charged particles inputtedto a resist film is forward-scattered, apart of the particles that havetransmitted the resist film are backward-scattered and it is inputtedthe resist film again. Thus, even when a charged particle beam isinputted to one point on the resist film, an area exposed by the chargedparticle is not only one point, but it also covers its neighborhood(proximity effect). Therefore, exposure data indicating the exposurepattern of a charged particle beam is usually formed by applyingproximity effect correction to layout data indicating a pattern to beformed on the resist film in order to optimize the amount of exposure ordimensions of an exposure pattern (Japanese Patent Application Nos.2005-101501, 2003-149784 and H11-8187).

With the recent fine semiconductor devices, the form of an exposurepattern for expose a semiconductor substrate has become fine and alsoits multi-layer structure has become complex. The backward scatterintensity of exposure to such a semiconductor substrate can becalculated with high accuracy by simulation based on a physical model(for example, simulation by a Monte Carlo method). However, actually ittakes a very long time to calculate the intensity. Thus, it is desiredto calculate the intensity in a shorter time while realizing higheraccuracy.

As publicly known, the scatter of a charged particle varies depending onits material. In the prior art disclosed by Japanese Patent ApplicationNo. 2005-101501 (hereinafter “patent reference 1”), scatter distributiondepending on a distance is prepared as a coefficient a and the backwardscatter intensity of each area is calculated by an area density method.If intensity in an area (i, j) is expressed Fb_(i, j), the Fb_(i, j) isfinally calculated as follows.

$\begin{matrix}{{Fb}_{i,j} = {\sum\limits_{l}{\sum\limits_{m}{{{E_{n - 1}\left( {{i + l},{{j + m};i},j} \right)} \cdot \alpha_{{i + l},{j + m}}}Q_{{i + l},{j + m}}}}}} & (1)\end{matrix}$

In the above equation, α_(i+1, j+m), Q_(i+1, j+m) and E_(n−1) (i+1, j+1;i, j) represent pattern density in an area (i+1, j+m), the amount ofexposure applied to an area (i+1, j+m) and a charged particle intensitycoefficient indicating the degree of influence on an area (i+1, j+m) ofthe amount of exposure applied to an area (i, j), respectively.

The charged particle intensity coefficient E_(n−1) corresponds to thecoefficient a. The coefficient a can be calculated using a reflectioncoefficient R, which is a ratio indicating the reflection of a chargedparticle on a layer, and a transmission coefficient T indicating itsratio of transmitting through the layer prepared by each material. Thus,the backward scatter intensity Fb_(i, j) taking the material of eachlayer into consideration can be calculated to realize high accuracy.This exposure data can also be appropriately generated in high accuracy.

In the manufacture of semiconductor devices, a factor of accuracydegradation due to a multi-layer structure, such as unevenness inthickness of lower layers, due to non-uniformity of chemical machinepolish (CMP) or the accuracy error in dimensions of the pattern of alower layer, sometimes occur. Stored energy distribution to the resistfilm varies depending on such a factor. Each value of the coefficients Rand T varies depending on the occurrence and the degree of such afactor. Thus, an error occurs in the backward scatter intensityFb_(i, j) which is calculated according to equation (1). The influenceof the error has a tendency to increase due to fine semiconductordevices. Therefore, in even wholly appropriate exposure data, aninappropriate point (poor resolution point) is easily detected byexposure verification. Thus, in the generation of exposure data,including exposure verification, it is also important to take such afactor of accuracy degradation into consideration.

In the prior art disclosed by Japanese Patent Application Nos.2003-149784 and H11-8187, the amount of calculation is reduced bylimiting a point for calculating stored energy including backwardscatter intensity as an evaluation point.

SUMMARY OF THE INVENTION

It is an object of the present invention to provide a technology forgenerating exposure data taking into consideration a factor of accuracydegradation due to a multi-layer structure.

The exposure data generation method of the present invention generatesexposure data for exposing a resist film formed on a multi-layeredsemiconductor substrate by a charge particle beam. The exposure datageneration method comprises obtaining exposure data indicating a patternto be exposed by the charge particle beam, which is generated fromlayout data indicating a pattern to be formed on the resist film,performing exposure verification the exposure data, using at least onechangeable coefficient, modifying the value of a coefficient when anerror point is extracted from the exposure data by exposure verificationand re-generating exposure data taking into consideration thecoefficient whose value is modified.

It is preferable to perform the exposure verification taking intoconsideration the backward scatter of the charged particle beam by alayer located below an exposure target layer on which a resist layer isformed. It is preferable to perform the exposure verification in twosteps; the first exposure verification using a coefficient and thesecond exposure verification performed based on the result of the firstexposure verification. The first exposure verification can also beperformed by calculating the degree of risk for approximating the sizeof the backward scatter intensity. It is preferable to perform at leastone of film thickness margin verification taking into consideration theerror of the film thickness of a layer constituting the semiconductorsubstrate and area density margin verification taking into considerationthe error of the dimensions of a pattern formed on the layer.

The exposure data verification methods in the first and second aspectsof the present invention both verify exposure data for exposing a resistfilm formed on a multi-layered semiconductor substrate by a chargedparticle beam and each of them performs exposure verification asfollows.

The exposure data verification method in the first aspect of the presentinvention calculates a plurality of the amount of exposure obtained onthe resist film taking into consideration the error in film thickness ofa layer constituting a semiconductor substrate and extracts a point tobe considered inappropriate from exposure data.

The exposure data verification method in the second aspect of thepresent invention calculates a plurality of the amount of exposureobtained on the resist film taking into consideration the error indimensions of a pattern formed on a layer constituting a semiconductorsubstrate and extracts a point to be considered inappropriate fromexposure data.

In the present invention, exposure verification is applied to exposuredata indicating a pattern to be exposed by a charge particle beam, usingat least one changeable coefficient. If the exposure verificationextracts an error point from the exposure data, the value of thecoefficient and exposure data is regenerated taking into considerationthe coefficient whose value is modified.

Some coefficient has an appropriate range taking into the factor ofaccuracy degradation due to a multi-layer structure. In exposureverification using such a coefficient, there is a possibility that theerror point varies depending on a value adopted for the exposureverification. By such a possibility, a point that is not actuallyerroneous sometimes regarded as an error point. However, if acoefficient value is changed within the appropriate range and exposuredata is re-generated, a point which should not be regarded as an errorpoint can be prevented or suppressed from being regarded as an errorpoint. Thus, an error point to be coped with can be more easily copedwith. As a result, exposure data can also be more easily generatedtaking into consideration the factor of accuracy degradation due to themulti-layer structure.

In the present invention, a plurality of the amount of exposure obtainedon a resist film can be calculated taking into consideration the errorin film thickness of a layer constituting a semiconductor substrate, anda point which should be regarded inappropriate can be extracted fromexposure data, based on the plurality of the calculated amount ofexposure. Therefore, a part which is made erroneous by a film thicknesserror can be surely extracted.

In the present invention, a plurality of the amount of exposure obtainedon a resist film can be calculated taking into consideration the errorin dimensions of a pattern formed on a layer constituting asemiconductor substrate, and a point which should be regardedinappropriate can be extracted from exposure data, based on theplurality of the calculated amount of exposure. Therefore, a part whichis made erroneous by a dimensional error of the formed pattern can besurely extracted.

Either of them facilitates coping with the factor of accuracydegradation due to a multi-layer structure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows the configuration of the exposure data generation device ofthe present invention;

FIG. 2 shows how to detect an error point in exposure verification;

FIG. 3 shows a correction parameter extraction data management table;

FIG. 4 shows a verification error management table;

FIG. 5A shows how to display an error when the error is detected by apattern edge resolution position error verification method;

FIG. 5B shows how to detect an error by the pattern edge resolutionposition error verification method;

FIG. 6A shows how to display an error when the error is detected by anexposure intensity contrast verification method;

FIG. 6B shows how to detect an error by the exposure intensity contrastverification method;

FIG. 7A shows how to display an error when the error is detected by anexposure amount margin verification method;

FIG. 7B shows how to detect an error by the exposure amount marginverification method;

FIG. 8A shows how to display an error when the error is detected by alower layer film thickness margin verification method;

FIG. 8B shows how to detect an error by the lower layer film thicknessmargin verification method;

FIG. 9A shows how to display an error when the error is detected by alower layer area density margin verification method;

FIG. 9B shows how to detect an error by the lower layer area densitymargin verification method;

FIG. 10 is the flowchart of the exposure data generation process; and

FIG. 11 shows an example of the hardware configuration of a computercapable of realizing the exposure data generation device of the presentinvention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The preferred embodiments of the present invention are described indetail below with reference to the drawings.

FIG. 1 shows the configuration of the exposure data generation device ofthe present invention.

The exposure data generation device generates exposure data by inputtingthe layout data of each layer, and if a point which should be poor(error point) is detected by exposure verification, the generationdevice re-generates exposure data in such a way as to correct the point.

An input unit 11 is used to externally input layout data and exposureexperiment data. In this preferred embodiment, exposure verification isperformed using the method disclosed by Patent reference 1. The exposureexperiment data is used to extract a coefficient needed for the exposureverification. Since the value of the coefficient is modified (updated)taking into consideration the factor of accuracy degradation due to amulti-layer structure, the coefficient is hereinafter called a“parameter”. In this case, a plurality of parameters exists.

A storage unit 12 stores various types of data inputted by the inputunit 11. A parameter extraction unit 13 extracts or modifies a parametervalue from the exposure experiment data. A proximity effect correctionunit 14 performs proximity effect correction using the parameter valueinputted from the parameter extraction unit 13 to generate exposuredata.

An exposure verification unit 15 applies exposure verification to thegenerated exposure data to extract an error point. The exposureverification unit 15 comprises a simple exposure verification unit 15 afor performing (simple) exposure verification using the method disclosedby Patent reference 1 and a detailed exposure verification unit 15 b forperforming exposure verification by Monte Carlo method.

Simple exposure verification is applied to the entire exposure datawhile detailed exposure verification is applied to an error pointdetected by the simple exposure verification. Thus, exposureverification which takes much calculation time can be minimized, andexposure data can be generated more rapidly while realizing highaccuracy.

If the error point extracted by simple exposure verification isconfirmed to be erroneous by detailed exposure verification, theexposure verification unit 15 stores the error point in the storage unit12 and instructs the parameter extraction unit 13 and the proximityeffect correction unit 14 to perform the process again. Thus, theparameter extraction unit 13 updates the parameter value within anappropriate range determined taking into consideration the factor ofaccuracy degradation due to a multi-layer structure in such a way as tocorrect the error point. The proximity effect correction unit 14re-generates exposure data after performing proximity effect correctionusing the updated parameter value.

The exposure verification unit 15 applies exposure verification to theregenerated exposure data again. If an error point is extracted again bythe exposure verification, the exposure verification unit 15 instructsthe parameter extraction unit 13 and the proximity effect correctionunit 14 to perform the process again. Thus, exposure data which includesno error point when the factor of accuracy degradation due to amulti-layer structure is taken into consideration is generated. Suchexposure data is outputted from an output unit 16.

FIG. 11 shows an example of the hardware configuration of a computercapable of realizing the exposure data generation device. Prior to thedetailed description of FIG. 1, the configuration of a computer capableof realizing the exposure data generation device is described in detail.For convenience' sake, the following description is made hereinafterpresuming that the exposure data generation device is realized by onecomputer with the configuration shown in FIG. 11.

The computer shown in FIG. 11 comprises a CPU 61, memory 62, an inputdevice 63, an output device 64, an external storage device 65, a storagemedium driving device 66 and a network connection device 67, which allare connected to each other by a bus 68. The configuration shown in FIG.11 is only one example and is not limited to this.

The CPU 61 is a central processing unit for controlling the entirecomputer.

The memory 62 is RAM or the like for temporarily storing a program ordata stored in the external storage device 65 (or portable storagemedium MD) when updating data or so on. The CPU 61 controls the entirecomputer by reading out the program into the memory 62 and executing it.

The input device 63 is connected to an input device, such as a keyboard,a mouse or the like or has it. The input device 63 detects the operatoroperation of such an input device and notifies the CPU 61 of thedetection result.

The output device 64 is connected to a display or the like or has it.The output device 64 outputs data transmitted under the control of theCPU 61 on the display.

The network connection device 67 is used to communicate with anotherdevice via a network, such as an intranet, the Internet or the like. Theexternal storage device 65 is a hard disk device or the like. Theexternal storage device 65 mainly stores various types of data andprograms.

The storage medium driving device 66 is used to access a portablestorage medium MD, such as an optical disk, a magneto-optical disk orthe like.

The layout data and the exposure experiment data are obtained via thenetwork connection device 67 or the storage medium driving device 66 andare stored in the external storage device 65 or the like. Thus, theinput unit 11 can be realized by the CPU 61, the memory 62, the externalstorage device 65, the network connection device 67, the storage mediumdriving device 66, and the bus 68. The storage unit 12 can be realizedby the external storage device 65 or the memory 62. The generatedexposure data is outputted via the network connection device 67 or thestorage medium driving device 66. Therefore, the output unit 16 can berealized by the CPU 61, the memory 62, the external storage device 65,the network connection device 67, the storage medium driving device 66,and the bus 68. The others can be realized by the CPU 61, the memory 62,the external storage device 65, and the bus 68.

The exposure data generation device (exposure data verification device)of this preferred embodiment can be realized by the CPU 61 executing theprogram mounting functions necessary for it. The program can be recordedin the storage medium MD and be distributed. Alternatively, it can beobtained by the network connection device 67.

FIG. 2 shows how to detect an error point in exposure verification. A“target graphic”, an “evaluation point” and a “resolution position”correspond to a pattern represented by layout data, a point to beverified, on the edge of the target graphic and an actually formedevaluation point on the pattern, respectively. In this preferredembodiment, basically an error point is extracted focused on thedeviation in a position between the resolution position and theevaluation point.

FIG. 3 shows a correction parameter extraction data management table.The correction parameter extraction data management table is stored inthe storage unit 12. The verification error management table shown inFIG. 4 is also stored in the storage unit 12. Hereinafter, thecorrection parameter extraction data management table and theverification error management table are called a “data management table”and an “error management table”, respectively.

The data management table is prepared to manage/store parameterextraction data. The data management table stores each coordinates ofthe evaluation point and resolution position for each data type. A“layout data identification name” in FIG. 3 indicates layout data towhich proximity effect correction is applied, that is, is an exposuredata identification name.

The parameter extraction unit 13 refers to data stored in the datamanagement table to determine the value of the parameter. For example,firstly, a parameter value such that the evaluation point and theresolution position is matched is extracted and determined. After that,a parameter value is extracted from newly stored data and an optimal oneis determined taking into consideration each extracted parameter. Theoptimal parameter value is determined by least squares method, forexample, using the first determined value as an initial value. As theparameter extraction method, the technology disclosed by Japanese PatentApplication No. 2005-211042, whose patent the applicant has applied forJul. 21, 2005 can be used.

Each parameter has an appropriate range. A parameter value must bedetermined taking the range into consideration. Thus, actually theparameter value is determined as follows.

In the backward scatter intensity calculation method disclosed by Patentreference 1, each of the transmission coefficient T, reflectioncoefficient R and diffusion length a indicating the 1/e radius ofGaussian distribution for each material of each layer has a physicalrange. The possible range of each parameter value of the film thicknessof 0˜∞ of a semiconductor substrate each layer of which is made of onekind of material is as follows.

0≈T≦1  (2)

0≦R≦η (backward scatter coefficient)  (3)

0≦σ≦βb (backward diffusion length)  (4)

Since the range of each parameter value is for fixed film thickness, therange can be narrowed to some extent by extracting each parameter in thefilm thickness by simulation or the like in advance.

If simulation by Monte Carlo method is used, usually scatter in the casewhere a film made of a target material is placed at the vacuum and a lotof charged particles (hereinafter called “electron”) is inputted to onepoint on its surface is simulated. In that case, the ratio of the totalenergy of electrons outputted from the surface of the film to the totalenergy of inputted electrons is the reflection coefficient R and astretch (1/e radius) obtained when the energy distribution of electronsoutputted from the surface of the film approximates Gaussiandistribution corresponds to the diffusion length σ. The ratio of thetotal energy of electrons outputted from the back surface of the film tothe total energy of inputted electrons corresponds to the transmissioncoefficient T. Strictly speaking, since the amount of energy ofelectrons and the stored amount of energy in the resist is not matched,some allowance must be given to each of the calculated parameters T_(o),R_(o) and σ_(o). Thus, a constant q indicating its allowance isexternally specified, and the range of each of the parameter values T, Rand σ is set according to the following expressions.

(1−q)T _(o) ≦T≦q+(1−q)T _(o)  (5)

(1−q)R _(o) ≦R≦qη+(1−q)R _(o)  (6)

(1−q)σ_(o) ≦σ≦qβb+(1−q)σ_(o)  (7)

If q=1, expressions (5)˜(7) coincide with expressions (2)˜(4). If q=0,they coincide with the values calculated by the simulation. Hereinafter,the lower and upper limits of the parameters are expressed as T_(min),R_(min) and σ_(min), and T_(man), R_(man) and σ_(man), respectively.

Firstly, each parameter value with an appropriate range indicated byexpressions (5)˜(7) is determined. The second time and after, thepreviously obtained value is corrected taking into consideration datanewly stored in the data management table. Thus, an optimal value in theneighborhood of the previously obtained value can be determined for theparameter.

In this case, the range of each parameter value is restricted to therange indicated by expressions (5)˜(7). However, if the number of thedata newly stored in the data management table is small, the change ofeach parameter value is expected to be small. Therefore, the previouslyapplied range can also be further narrowed around the initial valueaccording to the ratio of the newly added data to the entire data. Inthat case, if the initial values are T_(k−1), R_(k−1) and σ_(k−1) andthe ratio of newly added data to the entire data is p, the possibleranges of parameter values this time T_(k), R_(k) and σ_(k) can also berestricted as follows.

pT _(min,k−1)+(1−p)T _(k−1) ≦T _(k) ≦pT _(max,k−1)+(1−p)T _(k−1)  (8)

pR _(min,k−1)+(1−p)R _(k−1) ≦R _(k) ≦pR _(max,k−1)+(1−p)R _(k−1)  (9)

pσ _(min,k−1)+(1−p)σ_(k−1)≦σ_(k) ≦pσ _(max,k−1)+(1−p)σ_(k−1)  (10)

If each parameter exists out of a predetermined range when least squaresmethod is used as a method for correcting the parameter value within therange, sometimes no square-sum x² becomes a minimum by existence of theparameter that a value is out of a range. Least squares methodcorresponds to calculating a set of parameter values in which square-sumx² becomes a minimum, using square-sum x² as the function of the set ofparameter values. In this case, if square-sum x²(α) is calculatedaccording to an expression which monotonously increases out of theboundary as follows, assuming that only one parameter value α is usedand its range is α1≦α≦α2, for convenience' sake, the range can be madeto include a minimum value without fail when calculate square-sum x²(α)in an expression to increase monotonous outside from a border from theborder.

x ²(α)(α1≦α≦α2)  (11)

x ²(α)+kα×(α1−α)(α<α1)  (12)

x ²(α)+kα×(α−α2)(α2<α)  (13)

In the above expressions, kα is a constant (>0) for speeding up thereturn of α from its deviation in the search of a minimum value byincreasing the difference of α to some extent. The value can also be 1.

The above method can also extend similarly even if a plurality ofparameter values exists. Therefore, by adopting this method, eachparameter value can be corrected (determined) within each predeterminedrange. By such correction, only an actual error point or a point withsuch a high possibility remains in the exposure data. As a result, thedeveloper can cope with a point to be coped with, thereby improving workefficiency and serviceability.

FIG. 4 shows a verification error management table.

This error management table is prepared to manage/store error pointsdetected by exposure verification. The error management table stores thecoordinates of an evaluation point, an outward direction evaluationvector, a resolution position error and its error contents for eacherror point.

An evaluation point is provided on an edge of a target graphic. For thisreason, the outward direction evaluation vector (hereinafter called an“outward vector”) indicates a vector which pass through the evaluationpoint from inside the target graphic and goes outward in unit vectors.Thus, for example, in FIG. 2, if there are the evaluation point and theresolution position on the X-axis and the resolution position is locatedin smaller coordinates than the revaluation point on the X-axis, theoutward vector becomes (1, 0). If they are located reversely on theX-axis, it becomes (−1, 0).

The resolution position error indicates the respective errors of theevaluation point and the resolution position in the outward vectordirection. Therefore, for example, similarly, if there are theevaluation point and the resolution position on the X-axis and theresolution position is located in smaller coordinates than therevaluation point on the X-axis, the resolution position error becomesnegative. Thus, if an error occurs in the thick direction of a targetgraphic, the resolution position error becomes positive. If an erroroccurs in the reverse direction, it becomes negative.

In this preferred embodiment, a plurality of types of exposureverification is attempted. Each of E1˜E3 shown in FIG. 4 indicates thetype of exposure verification which detects an error. The exposureverification performed in this preferred embodiment is specificallydescribed below with reference to FIGS. 5A˜9B.

FIGS. 5A and 5B shows a pastern edge resolution position errorverification method. FIG. 5A shows how to display an error when theerror is detected by the pattern edge resolution position errorverification method. FIG. 5B shows how to detect an error by the patternedge resolution position error verification method.

In FIG. 5A, the resolution position Δ is located on the left of theevaluation point. Hereinafter, in FIGS. 6A˜9A too, it is assumed forconvenience' sake that the direction where the resolution position Δ andthe evaluation point are arrayed is the X-axis. The direction from theresolution position Δ toward the evaluation point is the ascendingdirection of a position on the X-axis. A direction where layers arepiled is called a vertical direction.

The vertical and horizontal axes of the graph shown in FIG. 5B indicateexposure intensity (amount of exposure) and a position on the X-axis,respectively. E_(th) represents the threshold of the exposure intensitywith which a pattern is formed. Δ_(max) represents the maximum value inthe allowance in the outward vector direction (the X-axis directionhere) using the evaluation point as the reference. Thus, the resolutionposition Δ range of −Δ_(max)≦Δ≦Δ_(max) is specified as its errorallowance and no error is detected in the range.

In FIG. 5A, the resolution position Δ is located far away from −Δ_(max).The error graphic shown in FIG. 5A notifies that an error occurs due toit, and can be displayed as a rectangle having a width on an edge (theY-axis here) covered by the evaluation point and a width (error) on theX-axis, of the evaluation point and the resolution position Δ. Data fordisplaying the error graphic can be outputted in the same file format asthe layout data, exposure data or the like.

FIGS. 6A and 6B shows an exposure intensity contrast verificationmethod. Like FIGS. 5A and 5B, FIG. 6A shows how to display an error whenthe error is detected by the exposure intensity contrast verificationmethod. FIG. 6B shows how to detect an error by the exposure intensitycontrast verification method.

In this exposure intensity contrast verification method, a contrastvalue C(=(E_(max)−E_(min))/(E_(max)+E_(min))) is calculated using themaximum exposure intensity E_(max) in a target graphic and the minimumexposure intensity E_(min) in the neighborhood of its outside. Whetheror not an error occurs is checked by whether the calculated value C isequal to or more than the threshold C_(min) which is predetermined asthe allowable minimum value. The width on the X-axis of the errorgraphic in the case where the error occurs is a width obtained bymultiplying a width with the target graphic adjacent on the X-axis,which has a corresponding evaluation point, by the value of 100−C.

FIGS. 7A and 7B shows an exposure amount margin verification method.Like FIGS. 5A and 5B, FIG. 7A shows how to display an error when theerror is detected by the exposure amount margin verification method.FIG. 7B shows how to detect an error by the exposure amount marginverification method.

Exposure intensity needed to form a pattern depends on the material ofan adopted resist film. This means that an actual edge position variesdepending on the material of a resist film. Therefore, in this exposureamount margin verification method, as shown in FIG. 7B, the maximumchange ratio k_(max) is prepared to set the allowable range of exposureintensity (amount of exposure). Then, two resolution positions Δ₁ andΔ₂, which are 1/(1−k_(max)) and 1/(1+k_(max)) respectively of anexposure intensity threshold E_(th) are calculated, and it is checkedwhether these resolution positions Δ₁ and Δ₂ both are within the errorallowance. The width on the X-axis of the error graphic are one betweenthose resolution positions Δ_(j) and Δ₂.

FIGS. 8A and 8B shows a lower layer film thickness margin verificationmethod. Like FIGS. 5A and 5B, FIG. 8A shows how to display an error whenthe error is detected by the lower layer film thickness marginverification method. FIG. 8B shows how to detect an error by the lowerlayer film thickness margin verification method.

Backward scatter intensity varies depending on not only a material butalso layer film thickness. If the parameter values are T, R and σ andtheir respective values in the case where the film thickness becomes ntimes are T_(n), R_(n) and σ_(n), the following relationship existsbetween those values. Therefore, exposure intensity varies depending onfilm thickness.

T_(n)=T^(n)  (14)

R _(n) =R(1−T _(n) ²)/(1−T ²)=R(1−T ^(2n))/(1−T ²)  (15)

σ_(n)=n^(1/2)σ  (16)

The film thickness varies depending on the non-uniformity of chemicalmachine polish (CMP). It also varies depending on its position on thesemiconductor substrate, its manufacturing process and the like. Forthis reason, in this lower layer film thickness margin verificationmethod, as shown in FIG. 8B, the maximum possible amount of change d ofthe film thickness of a lower layer is taken into consideration. In eachof the case where the film is thick by the maximum amount of change dand the case where the film is thin by the maximum amount of change d,resolution positions Δ₁ and Δ₂ whose exposure intensity is the thresholdE_(th) are calculated and it is checked whether those resolutionpositions Δ₁ and Δ₂ both are within its error allowance. Since it can beconsidered that an actual resolution position exists between thoseresolution positions Δ₁ and Δ₂, an error due to the error of filmthickness can be surely detected. In this case, the width on the X-axisof an error graphic is one between the evaluation point and theresolution position Δ₂.

FIGS. 9A and 9B shows a lower layer area density margin verificationmethod. Like FIGS. 5A and 5B, FIG. 9A shows how to display an error whenthe error is detected by the lower layer area density marginverification method. FIG. 9B shows how to detect an error by the lowerlayer area density margin verification method.

Backward scatter intensity varies depending on a material. The areadensity of the lower layer area density margin verification methodvaries depending on an error in pattern generation. For example, asshown in FIG. 9B, if an object indicated by a rectangle in the top viewof a layer is a contact hole, it can be considered that the maximumamount of change d exists in the width (dimensions) of the contact hole.If such an amount of change d exists, exposure intensity varies betweenthe case where the dimensions is thick by the maximum amount of change dand the case where the dimensions is thin by the maximum amount ofchange d. For this reason, in this lower layer area density marginverification method, as shown in FIG. 9B, the maximum possible amount ofchange d of the dimensions of a pattern formed on a lower layer is takeninto consideration. Then, two resolution positions Δ₁ and Δ₂, which arethe case where the dimensions is thick by the maximum amount of change dand the case where the dimensions is thin by the maximum amount ofchange d, respectively of an exposure intensity threshold E_(th) arecalculated, and it is checked whether these resolution positions Δ₁ andΔ₂ both are within the error allowance. Since it can be considered thatan actual resolution position exists between those resolution positionsΔ₁ and Δ₂, an error due to an error in the dimensions of a formedpattern can be surely detected. In this case, the width on the X-axis ofan error graphic is one between the evaluation point and the resolutionposition Δ₂.

E1-3 shown in FIG. 4 indicate errors detected by the pattern edgeresolution position error verification method, the exposure intensitycontrast verification method and the exposure amount margin verificationmethod, respectively. In their parentheses of symbols “E1”, “E2” and“E3”, an error from the evaluation point of the resolution position Δ,contrast value C and errors from the evaluation point of two resolutionpositions Δ₁ and Δ₂, respectively are shown.

In the exposure verification unit 15, each of the simple exposureverification unit 15 a and the detailed exposure verification unit 15 bperform exposure verification using the various types of verificationmethods described above. Thus, exposure data is generated by modifyingparameter values while avoiding the actual occurrence of an error withhigh accuracy.

FIG. 10 is the flowchart of the exposure data generation process. Next,the process of generating exposure data and its flow are described indetail with reference to FIG. 10. The generation process can berealized, for example, by the CPU 61 shown in FIG. 11 executing aprogram stored in the external storage device 65 or a storage medium MD.Thus, the exposure data generation device of the present invention canbe realized by the computer whose configuration is shown in FIG. 11executing the program. Here, the following description assumes that theexternal storage device 65 (storage unit 12) stores layout data D1 andexposure experiment data.

Firstly, in step S1, the layout data D1 is read from the externalstorage device 65 and layout data of an exposure target layer and itslower layer is extracted. In step S2, the correction parameterextraction data management table (FIG. 3) is stored in an area securedin RAM 62 or the like. Then, the exposure experiment data 2 is read fromthe external storage device 65 and is registered in the table.

In step S3, parameter values are extracted from the data stored in thedata management table. In step S4, proximity effect correction isapplied to the layout data of the exposure target layer using theextracted parameter values to generate exposure data. In step S5, awindow process is applied to the entire exposure verification area(exposure data) to extract the importance point of design.

In this window process, its design rules are checked and a pointrequiring high accuracy is extracted as the importance point of design.

In step S6, simple exposure verification is performed to extract anerror point. Then, the extracted error point is registered in theverification error management table (FIG. 4). In step S7, detailedexposure verification is applied to the error point registered in theerror management table, and a point that is not determined to beerroneous by the verification is deleted from the error managementtable.

In step S8, it is determined whether the process termination criterionis met. If no error point is registered in the error management table,if no change exists in the registered error or if a parameter valuecannot be updated within a predetermined range, it is determined thatthe process termination criterion is met and its determination is yes.Then, lastly, in step S9, the exposure data D3 that is generated whenperforming step S4 is outputted and the series of processes terminate.Otherwise, its determination is no and the flow proceeds to step S10. Instep S10, the error point registered in the error management table isregistered in the data management table and the flow returns to step S3.

In step S3, the parameter values are updated (corrected) taking intoconsideration the data (error point) added to the data management table.In step S4, exposure data is re-generated. In step S5, the windowprocess is applied only to the error point registered in the errormanagement table and then the error management table is cleared (initialsetting). In this way, the second time and after, in steps S3˜S5,processes whose contents are different from those of the first time areperformed. In step S6, since simple exposure verification can beperformed in high speed, the simple exposure verification is applied tothe entire exposure verification area. However, the simple exposureverification can also be applied only to the point extracted by thewindow process.

In the multi-layered semiconductor device, the above described exposuredata generation process is performed for each layer. Thus, appropriateexposure data can be obtained for each layer.

Although in this preferred embodiment, the method disclosed by Patentreference 1 is adopted as the simple exposure verification method (forthe calculation of the backward scatter intensity), another method canalso be adopted. Since, for example, in a point greatly influenced bybackward scatter, the exposure intensity is high in a non-exposure part,the amount of exposure must be reduced in an exposure part. As a result,resolution (contrast) tends to degrade. For that reason, such a point issometimes called the degree of risk as a simple evaluation index. Thedegree of risk corresponds to the size of backward scatter intensity,that is, approximates the size. The degree of risk (i, j) of an area (i,j) is calculated as follows. In the following equation, “α_(k)(i, j)”and “(1−α_(k)(i, j))” are the pattern area density of a heavy materialin a layer k and that of a light material, respectively.

$\begin{matrix}{{{Degree}\mspace{14mu} {of}\mspace{14mu} {{risk}\left( {i,j} \right)}} = {\prod\limits_{k = 1}^{N}{\left\lbrack {{C_{k}{\alpha_{k}\left( {i,j} \right)}} + {D_{k}\left\{ {1 - {\alpha_{k}\left( {i,j} \right)}} \right\}}} \right\rbrack \mathcal{M}}}} & (17)\end{matrix}$

When the surface of the semiconductor substrate is the same in asufficiently wide range, the size of the backward scatter intensity hasthe following tendency.

(1) The higher the ratio of a heavy material (corresponding to a patternarea density) is, the larger the backward scatter intensity is.(2) The thicker the thickness of a heavy material is, the larger thebackward scatter intensity is.There is a relationship of C_(k)>D_(k) between coefficients C_(k) andD_(k) which are multiplied to α_(k)(i, j) and (1−α_(k)(i, j)),respectively, due to the tendency (1). Therefore, the larger the numberof layers containing a heavy material, the higher the degree of riskbecomes. Thus, the tendency (2) is also taken into consideration. Forexample, if in the case of two-layered semiconductor substrate, 100% ofa heavy material and 100% of a light material exist in the first andsecond layers, the degree of risk becomes C₁×D₂. If 100% of a heavymaterial also exists in the second layer, the degree of risk becomesC₁×C₂. Since C₂>D₂, in this example, the degree of risk of the latter ishigher. Thus, in the calculated degree of risk, the tendencies (1) and(2) both are taken into consideration. Therefore, it can be used tospecify an error point or a point with such a possibility.

The appropriate value of each of the coefficients C_(k) and D_(k) variesdepending on film thickness and area density (pattern dimensions, etc.)like the parameters T, R and σ and has an appropriate range. For thisreason, even when the degree of risk is used for exposure verification,as a whole, each process can be performed according to the flow shown inFIG. 10.

1-6. (canceled)
 7. An exposure data generation method for generatingexposure data for exposing a resist film formed on a multi-layeredsemiconductor substrate by a charged particle beam, comprising:calculating a plurality of amounts of exposure obtained on the resistfilm taking into consideration an error caused in dimensions of apattern formed on a layer constituting the semiconductor substrate; andextracting a point to be inappropriate from the exposure data, based onthe plurality of calculated amounts of exposure. 8-9. (canceled)
 10. Anexposure data verification device for verifying exposure data forexposing a resist film formed on a multi-layered semiconductor substrateby a charged particle beam, comprising: calculation unit for calculatinga plurality of amounts of exposure obtained on the resist film takinginto consideration an error caused in dimensions of a pattern formed ona layer constituting the semiconductor substrate; and exposureverification unit for performing exposure verification for extracting apoint to be inappropriate from the exposure data, based on the pluralityof calculated amounts of exposure by the calculation unit. 11-12.(canceled)
 13. A computer-readable storage medium on which is recorded aprogram for enabling a computer to perform functions, the functionscomprising: calculation function for calculating a plurality of amountsof exposure obtained on the resist film taking into consideration anerror caused in dimensions of a pattern formed on a layer constitutingthe semiconductor substrate; and exposure verification function forperforming exposure verification for extracting a point to beinappropriate from the exposure data, based on the plurality ofcalculated amounts of exposure by the calculation function.